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Ulf Schmitz, Introduction to genomics and proteomics II 1 www. .uni-rostock. Bioinformatics Bioinformatics Introduction to genomics and proteomics II Introduction to genomics and proteomics II [email protected] Bioinformatics and Systems Biology Group www.sbi.informatik.uni-rostock.de

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Page 1: Www..uni-rostock.de Ulf Schmitz, Introduction to genomics and proteomics II1 Bioinformatics Introduction to genomics and proteomics II ulf.schmitz@informatik.uni-rostock.de

Ulf Schmitz, Introduction to genomics and proteomics II 1

www. .uni-rostock.de

BioinformaticsBioinformaticsIntroduction to genomics and proteomics IIIntroduction to genomics and proteomics II

[email protected]

Bioinformatics and Systems Biology Groupwww.sbi.informatik.uni-rostock.de

Page 2: Www..uni-rostock.de Ulf Schmitz, Introduction to genomics and proteomics II1 Bioinformatics Introduction to genomics and proteomics II ulf.schmitz@informatik.uni-rostock.de

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Outline

1. Proteomics• Motivation• Post -Translational Modifications• Key technologies• Data explosion

2. Maps of hereditary information

3. Single nucleotide polymorphisms

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Protomics

Proteomics:• is the large-scale study of proteins, particularly their structures and functions• This term was coined to make an analogy with genomics, and is often viewed as the "next step",• but proteomics is much more complicated than genomics. • Most importantly, while the genome is a rather constant entity, the proteome is constantly changing through its biochemical interactions with the genome. • One organism will have radically different protein expression in different parts of its body and in different stages of its life cycle.

Proteome: The entirety of proteins in existence in an organism are

referred to as the proteome.

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Proteomics

If the genome is a list of the instruments in an orchestra, the proteome is the orchestra playing a symphony.R.Simpson

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Proteomics

• Describing all 3D structures of proteins in the cell is called Structural Genomics

• Finding out what these proteins do is called Functional Genomics

GENOME

PROTEOME

DNA Microarray Genetic Screens

Protein – Ligand Interactions

Protein – Protein Interactions

Structure

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Proteomics

• What kind of data would we like to measure?

• What mature experimental techniques exist to determine them?

• The basic goal is a spatio-temporal description of the deployment of proteins in the organism.

Motivation:

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Proteomics

• the rates of synthesis of different proteins vary among different tissues and different cell types and states of activity

• methods are available for efficient analysis of transcription patterns of multiple genes

• because proteins ‘turn over’ at different rates, it is also necessary to measure proteins directly

• the distribution of expressed protein levels is a kinetic balance between rates of protein synthesis and degradation

Things to consider:

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Why do Proteomics?• are there differences between amino acid sequences determined

directly from proteins and those determined by translation from DNA?– pattern recognition programs addressing this questions have following

errors:• a genuine protein sequence may be missed entirely• an incomplete protein may be reported• a gene may be incorrectly spliced• genes for different proteins may overlap• genes may be assembled from exons in different ways in different tissues

– often, molecules must be modified to make a mature protein that differs significantly from the one suggested by translation

• in many cases the missing post-translational- modifications are quite important and have functional significance

• post-transitional modifications include addition of ligands, glycosylation, methylation, excision of peptides, etc.

– in some cases mRNA is edited before translation, creating changes in the amino acid sequence that are not inferrable from the genes

• a protein inferred from a genome sequence is a hypothetical object until an experiment verifies its existence

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Post-translational modification• a protein is a polypeptide chain composed of 20 possible amino acids

• there are far fewer genes that code for proteins in the human genome than there are proteins in the human proteome (~33,000 genes vs ~200,000 proteins).

• each gene encodes as many as six to eight different proteins– due to post-translational modifications such as phosphorylation, glycosylation or cleavage

(Spaltung)

• posttranslational modification extends the range of possible functions a protein can have– changes may alter the hydrophobicity of a protein and thus determine if the modified protein is

cytosolic or membrane-bound– modifications like phosphorylation are part of common mechanisms for controlling the behavior of

a protein, for instance, activating or inactivating an enzyme.

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www. .uni-rostock.dePost-translational modification

• phosphorylation is the addition of a phosphate (PO4) group to a protein or a small molecule (usual to serine, tyrosine, threonine or histidine)

• In eukaryotes, protein phosphorylation is probably the most important regulatory event

• Many enzymes and receptors are switched "on" or "off" by phosphorylation and dephosphorylation

• Phosphorylation is catalyzed by various specific protein kinases, whereas phosphatases dephosphorylate.

Phosphorylation

Acetylation• Is the addition of an acetyl group, usually at the N-terminus of the protein

Farnesylation• farnesylation, the addition of a farnesyl group

Glycosylation • the addition of a glycosyl group to either asparagine, hydroxylysine,

serine, or threonine, resulting in a glycoprotein

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Proteomics

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Key technologies for proteomics

1. 1-D electrophoresis and 2-D electrophoresis • are for the separation and visualization of proteins.

2. mass spectrometry, x-ray crystallography, and NMR (Nuclear magnetic resonance ) • are used to identify and characterize proteins

3. chromatography techniques especially affinity chromatography • are used to characterize protein-protein interactions.

4. Protein expression systems like the yeast two-hybrid and FRET (fluorescence resonance energy transfer) • can also be used to characterize protein-protein interactions.

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Key technologies for proteomics

Reference map of lympphoblastoid cell linePRI, soluble proteins. • 110 µg of proteins loaded• Strip 17cm pH gradient 4-7, SDS PAGE gels 20 x 25 cm, 8-18.5% T. • Staining by silver nitrate method (Rabilloud et al.,)• Identification by mass spectrometry. The pinks labels on the spots indicate the ID in Swiss-prot database

browse the SWISS-2DPAGE database for more 2d PAGE images

High-resolution two-dimensional polyacrylamide gel electrophoresis (2D PAGE) shows the pattern of protein content in a sample.

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Proteomics

Typically, a sample is purified to homogeneity, crystallized, subjected to an X-ray beam and diffraction data are collected.

X-ray crystallography is a means to determine the detailed molecular structure of a protein, nucleic acid or small molecule.

With a crystal structure we can explain the mechanism of an enzyme, the binding of an inhibitor, the packing of protein domains, the tertiary structure of a nucleic acid molecule etc..

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High-throughput Biological Data

• Enormous amounts of biological data are being generated by high-throughput capabilities; even more are coming– genomic sequences– gene expression data (microarrays)– mass spec. data– protein-protein interaction (chromatography)– protein structures (x-ray christallography)– ......

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www. .uni-rostock.deProtein structural data explosionProtein Data Bank (PDB): 33.367 Structures (1 November 2005)28.522 x-ray crystallography, 4.845 NMR

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Maps of hereditary information

1. Linkage maps of genes mini- / microsatellites

2. Banding patterns of chromosomes physical objects with visible landmarks called banding patterns

3. DNA sequences Contig maps (contigous clone maps) Sequence tagged site (STS) SNPs (Single nucloetide polymorphisms)

Following maps are used to find out how hereditary information is stored, passed on, and implemented.

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Linkage map

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Maps of hereditary information

• regions, 8-80bp long, repeated a variable number of times• the distribution and the size of repeats is the marker• inheritance of VNTRs can be followed in a family and

mapped to a pathological phenotype• first genetic data used for personal identification

– Genetic fingerprints; in paternity and in criminal cases

Variable number tandem repeats (VNTRs, also minisatellites)

Short tandem repeat polymorphism (STRPs, also microsatellites)

• Regions of 2-7bp, repeated many times– Usually 10-30 consecutive copies

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centromere

CGTCGTCGTCGTCGTCGTCGTCGT...GCAGCAGCAGCAGCAGCAGCAGCA...

3bp

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Maps of hereditary information

Banding patterns of chromosomes

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Maps of hereditary information

Banding patterns of chromosomes

petite – armcentromere

queue - arm

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Maps of hereditary information

• Series of overlapping DNA clones of known order along a chromosome from an organism of interest, stored in yeast or bacterial cells as YACs (Yeast Artificial Chromosomes) or BACs (Bacterial Artificial Chromosomes)

• A contig map produces a fine mapping (high resolution) of a genome

• YAC can contain up to 106bp, a BAC about 250.000bp

Contig map (also contiguous clone map)

Sequence tagged site (STS)

• Short, sequenced region of DNA, 200-600bp long, that appears in a unique location in the genome

• One type arises from an EST (expressed sequence tag), a piece of cDNA

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Maps of hereditary information

1. if we know the protein involved, we can pursue rational approaches to therapy

2. if we know the gene involved, we can devise tests to identify sufferers or carriers

3. wereas the knowledge of the chromosomal location of the gene is unnecessary in many cases for either therapy or detection; • it is required only for identifying the gene, providing a

bridge between the patterns of inheritance and the DNA sequence

Imagine we know that a disease results from a specific defective protein:

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Single nucleotide polymorphisms (SNPs)Single nucleotide polymorphisms (SNPs)

• SNP (pronounced ‘snip’) is a genetic variation between individuals

• single base pairs that can be substituted, deleted or inserted

• SNPs are distributed throughout the genome– average every 2000bp

• provide markers for mapping genes• not all SNPs are linked to diseases

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www. .uni-rostock.deSingle nucleotide polymorphisms (SNPs)

• nonsense mutations: – codes for a stop, which can truncate the

protein

• missense mutations: – codes for a different amino acid

• silent mutations: – codes for the same amino acid, so has no

effect

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Outlook – coming lecture

• Bioinformatics Information Resources And Networks– EMBnet – European Molecular Biology Network

• DBs and Tools

– NCBI – National Center For Biotechnology Information• DBs and Tools

– Nucleic Acid Sequence Databases – Protein Information Resources– Metabolic Databases– Mapping Databases– Databases concerning Mutations– Literature Databases

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Thanks for your attention!